Resource Allocation for Wireless Distributed Computing Networks

Abstract

Wireless distributed computing networks (WDCNs) will become the next frontier of the wireless industry as the performance of wireless platforms is being increased every year and wireless industries are looking for "killer" applications for increased channel capacity. However, WDCNs have several unique problems compared with currently well-investigated methods for wireless sensor networks and wired distributed computing. For example, it is difficult for WDCNs to be power/energy efficient considering the uncertainty and heterogeneity of the wireless environment. In addition, the service model has to take account of the interference-limited feature of wireless channels to reduce the service delay. Our research proposes a two-phase model for WDCNs including the service provision phase and the service access phase according to different traffic patterns and performance requirements. For the service provision phase, we investigate the impact of communication channel conditions on the average execution time of the computing tasks within WDCNs. We then discuses how to increase the robustness and power efficiency for WDCNs subject to the impact of channel variance and spatial heterogeneity. A resource allocation solution for computation oriented WDCNs is then introduced in detail which mitigates the effects of channel variations with a stochastic programming solution. Stochastic geometry and queue theory are combined to analyze the average performance of service response time and to design optimal access strategies during the service access phase. This access model provides a framework to analyze the service access performance and evaluate whether the channel heterogeneity should be considered. Based on this analysis, optimal strategies to access the service nodes can be determined in order to reduce the service response time. In addition, network initialization and synchronization are investigated in order to build a multiple channel WDCN in dynamic spectrum access (DSA) environments. Further, an efficient primary user detection method is proposed to reduce the channel vacation latency for WDCNs in DSA environments. Finally, this dissertation presents the complete design and implementation of a WDCN on COgnitive Radio Network (CORNET). Based on SDR technologies, software dedicated to WDCNs is designed and implemented across the PHY layer, MAC layer, and application layer. System experiments are carried out to demonstrate the performance issues and solutions presented in this dissertation. Wireless distributed computing networks (WDCNs) will become the next frontier of the wireless industry as the performance of wireless platforms is being increased every year and wireless industries are looking for "killer" applications for increased channel capacity. However, WDCNs have several unique problems compared with currently well-investigated methods for wireless sensor networks and wired distributed computing. For example, it is difficult for WDCNs to be power/energy efficient considering the uncertainty and heterogeneity of the wireless environment. In addition, the service model has to take account of the interference-limited feature of wireless channels to reduce the service delay. Our research proposes a two-phase model for WDCNs including the service provision phase and the service access phase according to different traffic patterns and performance requirements. For the service provision phase, we investigate the impact of communication channel conditions on the average execution time of the computing tasks within WDCNs. We then discuses how to increase the robustness and power efficiency for WDCNs subject to the impact of channel variance and spatial heterogeneity. A resource allocation solution for computation oriented WDCNs is then introduced in detail which mitigates the effects of channel variations with a stochastic programming solution. Stochastic geometry and queue theory are combined to analyze the average performance of service response time and to design optimal access strategies during the service access phase. This access model provides a framework to analyze the service access performance and evaluate whether the channel heterogeneity should be considered. Based on this analysis, optimal strategies to access the service nodes can be determined in order to reduce the service response time. In addition, network initialization and synchronization are investigated in order to build a multiple channel WDCN in dynamic spectrum access (DSA) environments. Further, an efficient primary user detection method is proposed to reduce the channel vacation latency for WDCNs in DSA environments. Finally, this dissertation presents the complete design and implementation of a WDCN on COgnitive Radio Network (CORNET). Based on SDR technologies, software dedicated to WDCNs is designed and implemented across the PHY layer, MAC layer, and application layer. System experiments are carried out to demonstrate the performance issues and solutions presented in this dissertation.